Triple Data Assurance Program
Background: Inaccurate CRM data can lead to serious consequences such as misallocation of resources and loss of business opportunities.
- Zams implementation methodology::
- Data cleansing phase:
- Setting up intelligences to periodically check for duplicate/incomplete records
- Automatic flagging of outliers (e.g. sudden increase in customer size)
- Input Control:
- Docking call recording tools (e.g. Gong) automatically generates notes and reduces manual entry errors
- Setting Validation Rules for Required Fields
- Output Validation:
- Automatic data consistency checks before key reports are generated
- Provide credibility scores for important predictive outcomes
- Data cleansing phase:
- Special security measures::
- Enable audit logs to track data changes
- Setting access rights to sensitive data (e.g., management-only view of predictive models)
- Regular automatic backups to designated storage
Compliance Note: This solution is SOC 2 Type II and GDPR compliant and has been adopted by customers in the financial/healthcare industry.
This answer comes from the articleZams: an AI Intelligent Body Platform for Automating Enterprise Sales and OperationsThe
May not be reproduced without permission:AI productivity tools " How do you prevent poor sales decisions due to data errors?
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